Institutional analysis and irregular warfare: Israel Defense Forces during the 33-Day War of 2006
Bibliographic record
Abstract
The new attention paid to ‘small wars’ does not seem to translate into a better adaptation of conventional armed forces to this type of conflicts. As illustrated by the IDF's inability to get a decisive edge against the Hezbollah during the 33-Day War, Israel is no exception to such difficulty to adapt. A number of analysts have concluded that, victim of its long experience gained through the Intifadas, Israel ‘over-adapted’ to irregular warfare. Applying a sociological framework inspired by the seminal work of Richard Scott, this study suggests that this view is, at best, arguable. Going beyond the classical military explanations by uncovering key sociopolitical forces that have shaped the Israeli defense institutions, this study proposes that the combination of a post-heroic society and unbalanced civil–military relations have led the Israeli military institution to opt for a conventional posture articulated around technocentric tenets, which are ultimately disregarding the true nature of the asymmetrical challenge presented by the Hezbollah.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".